xdiss {mvpart} | R Documentation |
The function computes extended dissimilarity indices which are for long gradients have better good rank-order relation with gradient separation and are thus efficient in community ordination with multidimensional scaling.
xdiss(data, dcrit = 1, dauto = TRUE, dinf = 0.5, method = "man", use.min = TRUE, eps = 1e-04, replace.neg = TRUE, big = 10000, sumry = TRUE, full = FALSE, sq = FALSE)
data |
Data matrix |
dcrit |
Dissimilarities < dcrit are considered to have no species in common
and are recalculated. |
dauto |
Automatically select tuning parameters – recommended. |
method |
Dissimilarity index |
use.min |
Minimum dissimilarity of pairs of distances used – recommended. |
dinf, eps, replace.neg, big |
Internal parameters – leave as is usually. |
sumry |
Print summary of extended dissimilarities? |
full |
Return the square dissimilarity matrix. |
sq |
Square the dissimilarities – useful for distance-based partitionong. |
The function knows the same dissimilarity indices as gdist
.
Returns an object of class distance with attributes "Size" and "ok". "ok" is TRUE if rows are not disconnected (De'ath 1999).
Glenn De'ath
De'ath, G. (1999) Extended dissimilarity: a method of robust estimation of ecological distances from high beta diversity data. Plant Ecology 144(2):191-199.
Faith, D.P, Minchin, P.R. and Belbin, L. (1987) Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69, 57-68.
data(spider) spider.dist <- xdiss(spider)